ngraph.opset5.lstm_cell

ngraph.opset5.lstm_cell(X: Union[_pyngraph.Node, int, float, numpy.ndarray], initial_hidden_state: Union[_pyngraph.Node, int, float, numpy.ndarray], initial_cell_state: Union[_pyngraph.Node, int, float, numpy.ndarray], W: Union[_pyngraph.Node, int, float, numpy.ndarray], R: Union[_pyngraph.Node, int, float, numpy.ndarray], B: Union[_pyngraph.Node, int, float, numpy.ndarray], hidden_size: int, activations: List[str] = None, activations_alpha: List[float] = None, activations_beta: List[float] = None, clip: float = 0.0, name: Optional[str] = None) _pyngraph.Node

Return a node which performs LSTMCell operation.

Parameters
  • X – The input tensor with shape: [batch_size, input_size].

  • initial_hidden_state – The hidden state tensor with shape: [batch_size, hidden_size].

  • initial_cell_state – The cell state tensor with shape: [batch_size, hidden_size].

  • W – The weight tensor with shape: [4*hidden_size, input_size].

  • R – The recurrence weight tensor with shape: [4*hidden_size, hidden_size].

  • B – The bias tensor for gates with shape: [4*hidden_size].

  • hidden_size – Specifies hidden state size.

  • activations – The list of three activation functions for gates.

  • activations_alpha – The list of alpha parameters for activation functions.

  • activations_beta – The list of beta parameters for activation functions.

  • clip – Specifies bound values [-C, C] for tensor clipping performed before activations.

  • name – An optional name of the output node.

Returns

The new node represents LSTMCell. Node outputs count: 2.